Abstract

Abstract Metal Injection Moulding (MIM) is widely utilized in various manufacturing industries due to its ability to produce near net shaped components in high volume without compromising surface finish and mechanical properties. Debinding is one of the most crucial phases in the MIM process, as it affects the final properties of the end product. The use of 316L SS is widespread especially in the medical industry, specifically for implants and metallic biomaterials due to its favourable combination of mechanical properties and biological consistency The present work deals with utilization of the Taguchi method to investigate the influence of solvent debinding parameters on the characteristics of injection moulded 316L stainless steel (316L SS) using thermoplastic rice starch binder as one of the binder components. In this study, the 316L SS powder along with a binder system consisting of Thermoplastic Rice Starch (TPRS), Polyethylene (PE), Palm Stearin (PS) and Stearic Acid (SA) were mixed for 1 hour at a speed of 50 rev/min and at a temperature of 150°C using a Z-blade mixer. The feedstock was then injection moulded using a vertical injection moulding machine with parameters of injection pressure, injection temperature and time and holding time of 7 bar, 160°C, 10 seconds and 25 seconds respectively. , this research was done utilizing the Taguchi approach to investigate the influence of solvent debinding parameters of injection molded 316L SS The effects of three solvent debinding parameters: solvent type, debinding time and debinding temperature were investigated to obtain the highest percentage of binder removal. The interactions of the parameters were laid out using the L 9 orthogonal array. It was found through ANOVA that solvent type had the most significant effects on solvent debinding, followed by debinding temperature and debinding time. The optimized solvent debinding parameters are solvent type of methanol, debinding temperature of 80°C and debinding time of 4 hours. The confirmation experiment however did not achieve the required range of expected result with a 3.80% error due to the unstable behaviour of the optimized solvent type, methanol.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call